Two-dimensional scatter plot

docs/api-reference/index.md

@@ -12,6 +12,7 @@
    slicer
    superplot
    inspector
+   scatter
    scatter3d
    xyplot
 ```
@@ -40,8 +41,13 @@
    graphics.figure1d
    graphics.figure2d
    graphics.figure3d
+   graphics.imagefigure
    graphics.ImageView
+   graphics.linefigure
    graphics.LineView
+   graphics.scatterfigure
+   graphics.ScatterView
+   graphics.scatter3dfigure
    graphics.Scatter3dView
    graphics.tiled
 ```

docs/api-reference/matplotlib.md

@@ -10,6 +10,7 @@
    backends.matplotlib.canvas.Canvas
    backends.matplotlib.line.Line
    backends.matplotlib.image.Image
+   backends.matplotlib.scatter.Scatter
    backends.matplotlib.static.StaticFig
    backends.matplotlib.interactive.InteractiveFig
    backends.matplotlib.tiled.Tiled

docs/conf.py

@@ -232,6 +232,7 @@
     'peeling-layers',
     'tiled-random-samples',
     'polar-plots',
+    'updating-scatter',
 ]
 nbsphinx_thumbnails = {
     os.path.join(notebook_root, notebook): os.path.join(

docs/gallery/index.ipynb

@@ -35,7 +35,8 @@
     "* [Interactive masking](interactive-masking.ipynb)\n",
     "* [Peeling off the layers](peeling-layers.ipynb)\n",
     "* [Tiled random sample histograms](tiled-random-samples.ipynb)\n",
-    "* [Polar plots](polar-plots.ipynb)"
+    "* [Polar plots](polar-plots.ipynb)\n",
+    "* [Updating scatter points](updating-scatter.ipynb)"
    ]
   }
  ],

docs/gallery/tiled-random-samples.ipynb

@@ -161,8 +161,7 @@
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "pygments_lexer": "ipython3"
   }
  },
  "nbformat": 4,

docs/gallery/updating-scatter.ipynb

@@ -0,0 +1,83 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "dfd6576d-c0ad-44cd-9f72-8d93b35b9632",
+   "metadata": {},
+   "source": [
+    "# Updating scatter points\n",
+    "\n",
+    "This notebook will show examples on how to update positions and colors of scatter points using interactive widgets."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dceddbd2-09ea-43cd-a9ba-0510ccfe1560",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import plopp as pp\n",
+    "import scipp as sc\n",
+    "import ipywidgets as ipw\n",
+    "%matplotlib widget\n",
+    "\n",
+    "a = pp.Node(pp.data.scatter())\n",
+    "b = pp.Node(pp.data.scatter(seed=2) * 10.0)\n",
+    "\n",
+    "slider = ipw.FloatSlider(min=0, max=60, value=30,\n",
+    "                         description='Position of orange group',\n",
+    "                         style={'description_width': 'initial'},\n",
+    "                         layout={'width': '500px'})\n",
+    "slider_node = pp.widget_node(slider)\n",
+    "\n",
+    "@pp.node\n",
+    "def move(da, x):\n",
+    "    out = da.copy(deep=False)\n",
+    "    out.coords['x'] = da.coords['x'] + sc.scalar(x, unit=da.coords['x'].unit)\n",
+    "    return out\n",
+    "\n",
+    "move_node = move(da=b, x=slider_node)\n",
+    "\n",
+    "f = pp.scatter({'a': a, 'b': move_node}, cbar=False)\n",
+    "f.bottom_bar.add(slider)\n",
+    "f.canvas.xrange = [-40, 100]\n",
+    "f"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ae71757f-b903-40eb-add8-528a0e7eb05b",
+   "metadata": {
+    "nbsphinx": "hidden"
+   },
+   "outputs": [],
+   "source": [
+    "# This cell is used to generate the thumbnail for the docs gallery.\n",
+    "# It is hidden from the online documentation.\n",
+    "f.save('../_static/gallery/updating-scatter-thumbnail.png')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

docs/user-guide/index.md

@@ -57,16 +57,22 @@ getting-started/saving-figures
 
 :::
 
-::::{grid-item-card} Slicer plot
-:link: plot-types/slicer-plot.ipynb
-:img-bottom: ../_static/plot-types/slicer-plot.png
+::::{grid-item-card} Scatter plot
+:link: plot-types/scatter-plot.ipynb
+:img-bottom: ../_static/plot-types/scatter-plot.png
 
 :::
 
 ::::
 
 ::::{grid} 3
 
+:::{grid-item-card} Slicer plot
+:link: plot-types/slicer-plot.ipynb
+:img-bottom: ../_static/plot-types/slicer-plot.png
+
+:::
+
 :::{grid-item-card} Inspector plot
 :link: plot-types/inspector-plot.ipynb
 :img-bottom: ../_static/plot-types/inspector-plot.png
@@ -79,6 +85,10 @@ getting-started/saving-figures
 
 :::
 
+::::
+
+::::{grid} 3
+
 :::{grid-item-card} Scatter 3D plot
 :link: plot-types/scatter3d-plot.ipynb
 :img-bottom: ../_static/plot-types/scatter3d-plot.png
@@ -97,6 +107,7 @@ plot-types/image-plot
 plot-types/slicer-plot
 plot-types/inspector-plot
 plot-types/super-plot
+plot-types/scatter-plot
 plot-types/scatter3d-plot
 ```
 

docs/user-guide/plot-types/image-plot.ipynb

@@ -26,7 +26,7 @@
    "source": [
     "## Basic image plot\n",
     "\n",
-    "As with one-dimensional data, plotting two-dimensional data is done using the [plot](../../reference/generated/plopp.plot.rst) function."
+    "As with one-dimensional data, plotting two-dimensional data is done using the [plot](../../generated/plopp.plot.rst) function."
    ]
   },
   {

docs/user-guide/plot-types/line-plot.ipynb

@@ -26,7 +26,7 @@
    "source": [
     "## Basic line plot\n",
     "\n",
-    "The most common way to plot data with Plopp is to use the [plot](../../reference/generated/plopp.plot.rst) function.\n",
+    "The most common way to plot data with Plopp is to use the [plot](../../generated/plopp.plot.rst) function.\n",
     "This can either be done using the `plopp.plot()` free function,\n",
     "or calling the `.plot()` method on a Scipp data object (both are equivalent)."
    ]